Health-related Quality of life of medical students during the COVID-19 pandemic: A cross-sectional study in Lebanon

Abstract

Objectives: This study aims to assess (i) the health-related Quality of Life (QoL) of medical students in Lebanon, (ii) its association with their general characteristics, and (iii) to investigate the combined effects of the predictors affecting the quality of life of students. Methods: An observational cross-sectional study was performed over three months, targeting 401 medical students from six universities. The 36-item Short Form survey was used to quantify the different QoL scores. Results: The physical component (PC) domains had higher scores than the mental component (MC) ones (70.2 vs. 55.9). Students aged 30 years or less had higher scores in all the PC domains than older students (70.9 vs. 59.3; p<0.010) but comparable scores in the MC domains (55.6 vs. 59.8; p>0.050). Single students had a significantly higher role-emotional score (63.5 vs. 49.0; p<0.050), and those studying in public universities had greater general health scores (57.7 vs. 53.7; p<0.050). Younger age significantly increased most of the health-related PC scores, and having chronic diseases decreased all the QoL scores except the mental health score. Conclusion: The QoL of medical students was negatively affected during the pandemic, particularly their mental health. Informed educational and health decisions are required to minimize this impact on their academic performance.

Keywords

Education quality of life students physical component mental component

Introduction

Several measures were taken globally to contain the spread of the coronavirus disease of 2019 (COVID-19), including lockdowns, travel restrictions, social distancing, and the closure of universities and schools (Koweyes et al., 2021; Fink et al., 2022). Alternative forms of education became essential, causing learning loss and disengagement with learning, in addition to inequalities between students due to a lack of resources, food insecurity, and health challenges (Reimers, 2022). Higher education in Lebanon, like in many other countries, was affected, and online learning became necessary to maintain adequate tuition (Alsoufi et al., 2020). Nevertheless, this transition to distance learning disrupted the lives of students and teachers (Baroud et al., 2022), who had a more positive perception of face-to-face education in terms of satisfaction, quality, and interaction (Nambiar, 2020). The reported challenges included limited experience, low connectivity, lack of online learning devices, and insufficient physical workplaces (Gómez-García et al., 2022).

In addition to the lack of academic support, social isolation affected students’ mental health and many were obliged to be separated from their families (Loades et al., 2020). Research found that students experienced higher stress, anxiety, and depression levels than in the pre-pandemic period (Racine et al., 2021). They also shared a substantial increase in uncertainty and fear of losing a family member, a loved one, or even their lives (Asbury et al., 2021; Elharake et al., 2022). Students in higher education endured emotional disorders, substantial concerns about their professional careers and studies, and financial constraints (Gómez-García et al., 2022; Reyes-Portillo et al., 2022). In particular, medical students were experiencing increasing anxiety (Chandratre, 2020) and had higher rates of mental issues, burnout, stress, and substance abuse (Molodynski et al., 2021). They were exposed to risk factors due to their extensive work in hospitals (Essangri et al., 2021), and the exhaustion of the health system (Hatem and Goossens, 2022). This made them more susceptible to the psychological consequences of the pandemic compared to same-age peers (Husnain 2017).

Moreover, the consecutive lockdowns and the prolonged school closure adversely influenced students’ physical health (Luciano et al., 2021). A significant decline in physical activities was reported in the literature (Rizal and Wibowo, 2022) in addition to a decrease in the time spent outdoors (Moore et al., 2020), an increase in screen time (Lawrence et al., 2022), and irregular sleep patterns (Maximova et al., 2022). An increase in body mass was reported in men, in total fat in women, and distribution of fat in both sexes (Chwałczyńska and Andrzejewski, 2021). Furthermore, a positive correlation was shown between physical activity and mental well-being (Maugeri et al., 2020). Since they were both affected during the pandemic, medical students’ Quality of Life (QoL) was correspondingly impacted.

Medical students’ overall health was also impacted due to the high risk of infection (Aebischer et al., 2020) and increased body pain leading to excessive use of analgesics (Yasmin et al., 2022). During the pandemic, the prevalence of depressive symptoms among university students was high in addition to financial challenges (Heumann et al., 2023). Moreover, medical students were directly involved in medical decision-making, which increased anxiety and burnout (Batra, 2023). Understanding the health and well-being implications on medical students allows better-informed decisions that can be applied in similar situations. In 2013, the 36-item Short Form (SF-36) survey was validated and used on medical students in Lebanon to exploit their QoL (Sabbah et al., 2013). Findings from the aforementioned study showed higher social functioning among younger age and lower mental health scores among women and smokers (Sabbah et al., 2013). Medical students were recruited as alternative resources due to the lack of medical staff and increase in healthcare demands (Ardakani et al., 2023). The imposed changes could have affected their QoL and may have long-term consequences. In this context, the present study aims to assess (i) the health-related QoL of medical students in Lebanon during the COVID-19 pandemic, (ii) its association with their general characteristics, and (iii) to investigate the combined effects of the predictors affecting the quality of life of students.

Methods

Study design

An observational cross-sectional study was carried out over a period of three months (August–October 2021), targeting medical students from six universities in Lebanon.

Study sample and sample size

Students were recruited from four faculties with no selection criteria based on sex, nationality, age, or ethnicity. These faculties were in both public (Lebanese university) and private universities (Lebanese American University, American University of Beirut, Saint Joseph University, Beirut Arabic University, and the University of Balamand). Since universities were closed during the first two months of data collection, students were targeted in their workplaces or internships in different hospitals. The sample size was determined using the Epi Info 7 software. The calculation assumed that the probability of having good mental and physical health was 50%. Considering a 95% confidence interval and a 5% acceptable margin of error, 401 participants were required, with a 5% loss to follow-up.

Data collection

Two pharmacists approached the students by explaining the study objectives orally and invited them to participate by filling out an online survey. The first page of the survey mentioned above included a written version of the objectives with an estimated 12 min to answer it.

Study tool

A validated questionnaire was used for data collection. It was available in English and Arabic based on the student’s preferences. The first part included questions about their general characteristics (sex, age (≤30 or >30), the governorate of residence, marital status, type of the university (public or private), faculty (public health, medical sciences, dentistry or pharmacy) and the academic year (1–2, 3–4, 5 or more). They were also asked if they smoked (cigarettes or shisha) and if they had any diagnosed comorbidities. In the second part, The SF-36 survey (validated on the Lebanese population) was used and the corresponding answers were afterward graded over 100. These questions will generate eight subscales as follows: 10 questions for physical functioning (PF), four questions for physical role (PR), two questions for bodily pain (BP), six questions for general health (GH), four questions for vitality (VT), two questions for social functioning (SF), three questions for role-emotional (RE), and five questions for mental health (MH). The first four scores lead to the physical composite score (PC) while the last four can be summed to create the mental composite score (MC). A minimum score of 0 represents the lowest QOL and a maximum of 100 represents the highest.

Statistical analysis

Statistical analyses were performed using Statistical Package for Social Sciences (SPSS Inc, Chicago, Illinois) Version 27. Categorical variables are presented through frequencies and percentages while the different scores are presented through means and standard deviations. Individual SF-36 items were recorded, summed, and transformed as recommended (Ware et al., 2001). The index had good reliability (Cronbach alpha of 0.913 and 0.898 for the PC and MC, respectively) and positive inter-item correlations. The skewness, minimum and maximum of each score are presented in addition to their percentiles (25th, 50th, and 75th). One-way analysis of variance (ANOVA) was performed to assess the relationship between the SF-36 scale scores and the general characteristics of the students. Multivariate analyses through linear regression models were conducted to evaluate the combined effect of predictors (attributes of the students) on SF-36 dimensions. The confusion variables considered were those with a statistically significant p-value (<0.05) in the ANOVA analysis.

Ethical considerations

The study protocol, survey, and consent form were reviewed and approved by the institutional review board of the faculty of pharmacy of the Lebanese University. Data were completely anonymous and non-identifiable. Written informed consent was obtained from each student. Participants were informed that they could withdraw their participation at any point during the interview and that their information will only be used for research purposes.

Results

General characteristics of the students

Overall, 424 students were approached and 401 agreed to participate in the study (94.6%). The general characteristics of the students are presented in Table 1. The sample included a slightly higher number of women (N = 217, 54.1%) than men (N = 184, 45.9%). Most students (93.3%) were less than 30 years of age. As regards the governorate of residence, participants were located in the eight Lebanese governorates with Mount Lebanon (19.7%), Beirut (16.7%), Nabatiyeh (13.2%), and Akkar (12.7%) accounting for the highest proportions. Eighty-three percent of students were single and the rest were married or engaged. Most students studied in private universities (68.6%) and 31.4% studied in public universities. Participants were studying in one of the four faculties: the faculty of public health (32.9%), the faculty of medical sciences (26.4%), the faculty of pharmacy (20.9%), and the faculty of dentistry (19.7%). A third of the participants were in their first two years of studies, 41.4% were in their third or fourth year and 25.2% were in their fifth year or more. Around 22% of students were smokers and 21.9% had existing chronic diseases.

Table 1.

Distribution of the general characteristics of the students.

		Total (N = 401)
		Frequency (%)
Sex	Man	184 (45.9%)
	Woman	217 (54.1%)
Age (years)	≤30	374 (93.3%)
	>30	27 (6.7%)
Governorate of residence	Mount Lebanon	79 (19.7%)
Governorate of residence	Beirut	67 (16.7%)
	Nabatiyeh	53 (13.2%)
	Akkar	51 (12.7%)
	South	44 (11.0%)
	Bekaa	43 (10.7%)
	North	38 (9.5%)
	Baalbeck/Hermel	26 (6.5%)
Marital status	Single	333 (83.0%)
Marital status	Married/engaged	68 (17.0%)
University	Public university	126 (31.4%)
University	Private university	275 (68.6%)
Faculty	Public health	132 (32.9%)
	Medical sciences	106 (26.4%)
	Pharmacy	84 (20.9%)
	Dentistry	79 (19.7%)
Academic year	1–2	134 (33.4%)
Academic year	3–4	166 (41.4%)
	5 or more	101 (25.2%)
Do you smoke?	Yes	89 (22.2%)
Do you have any comorbidity?	Yes	88 (21.9%)

Results are given in terms of frequency (percentage).

Quality of life of medical students

Table 2 represents the mean score of each of the SF-36 survey domains, maximum, minimum, and percentiles (25th, 50th, and 75th). All scales had a high level of internal consistency reliability coefficient. A higher overall score for the physical components was noted (70.2 (20.1)) in comparison to the total score of the mental components (55.9 (23.9)). The median values were 73.7 and 56.7 for the PC and MC, respectively. Among the PC, PF had the highest mean (83.3) and GH had the lowest one (54.9) while between the MC, the VT, and MH scales had the lowest means (50.4 and 54.4, respectively).

Table 2.

Health-related quality of life of medical students: scores of the different domains.

	Physical components (PC)
	PF	PR	BP	GH	Total score
N	401	401	401	401	401
K^a	10	4	2	6	22
Mean (SD)	83.3 (23.5)	71.1 (36.1)	71.4 (28.1)	54.9 (14.9)	70.2 (20.1)
Skewness (SE)	−1.7 (0.1)	−0.9 (0.1)	−0.6 (0.1)	−0.3 (0.1)	−0.9 (0.1)
Minimum	0.0	0.0	0.0	0.0	0.0
Maximum	100.0	100.0	100.0	95.0	98.75
Percentiles
25th	80.0	50.0	55.0	50.0	58.4
50th (Median)	95.0	75.0	77.0	55.0	73.7
75th	100.0	100.0	100.0	65.0	87.5
	Mental components (MC)
	VT	SF	RE	MH	Total score
N	401	401	401	401	401
K^a	4	2	3	5	14
Mean (SD)	50.4 (22.2)	57.9 (28.2)	61.0 (33.9)	54.4 (20.7)	55.9 (23.9)
Skewness (SE)	0.2 (0.1)	−0.1 (0.1)	−0.4 (0.1)	0.2 (0.1)	−0.1 (0.1)
Minimum	0.0	0.0	0.0	0.0	0.0
Maximum	100.0	100.0	100.0	100.0	99.0
Percentiles
25th	35.0	38.7	0.0	40.0	36.8
50th (Median)	50.0	55.0	100.0	52.0	56.7
75th	65.0	80.0	100.0	68.0	73.2

^aNumber of items per scale. SD: Standard Deviation; SE: Standard Error.

Association between the health-related quality of life scores and the general characteristics of the students

The association between the health-related quality of life scores of the PC and the general characteristics of the students is shown in Table 3. No significant differences were noted between any of the PC scores and the sex, marital status, academic year, and smoking status of the students (p > 0.050). Nonetheless, students aged 30 years and less had significantly higher scores on all of the PC compared to those older than 30. In addition, students attending public universities had a higher GH score compared to those in private universities. Significant associations were noted between the BP and GH scores and the faculty attended by students. Those in medical sciences and pharmacy faculties had higher scores than those in public health and dentistry faculties. Moreover, students with no comorbidities had significantly higher PR, BP, GH, and total PC scores.

Table 3.

Association between the health-related quality of life scores of the physical components and the general characteristics of the students.

	Physical components
	PF	PR	BP	GH	Total score
Sex
Man	83.5 (24.1)	72.3 (36.1)	69.8 (28.3)	54.8 (14.1)	70.1 (20.3)
Woman	83.1 (23.1)	70.0 (36.2)	72.7 (27.8)	55.1 (15.6)	70.2 (20.0)
F	0.021	0.381	1.059	0.029	0.005
Age
≤30	84.0 (23.5)	72.1 (35.6)	72.4 (27.3)	55.3 (14.9)	70.9 (19.7)
>30	73.5 (22.0)	56.5 (40.2)	57.2 (34.2)	50.0 (14.1)	59.3 (23.3)
F	5.022*	4.768*	7.515**	3.229*	8.608**
Marital status
Single	83.9 (23.6)	72.5 (34.7)	71.3 (28.1)	55.1 (15.3)	70.7 (19.7)
Married/Engaged	80.0 (23.2)	63.9 (41.7)	71.7 (28.0)	54.2 (12.9)	67.5 (21.1)
F	1.582	3.182	0.009	0.225	1.493
University
Public	85.8 (21.8)	72.8 (34.6)	74.1 (23.5)	57.7 (12.8)	72.6 (15.6)
Private	82.1 (24.2)	70.3 (36.8)	70.1 (29.8)	53.7 (15.7)	69.1 (21.8)
F	2.126	0.428	1.761	6.005*	2.678
Faculty
Public health	81.9 (24.9)	70.4 (35.1)	67.9 (29.3)	52.9 (14.5)	68.3 (20.2)
Medical sciences	87.4 (19.6)	70.3 (39.1)	76.5 (26.6)	57.4 (13.9)	72.9 (19.4)
Dentistry	82.5 (22.1)	69.0 (36.5)	65.2 (29.2)	51.9 (15.0)	67.2 (21.8)
Pharmacy	80.8 (26.5)	75.0 (33.8)	76.3 (25.0)	57.9 (15.9)	72.5 (18.9)
F	1.598	0.447	4.048**	4.064**	2.016
Academic year
1–2	81.3 (25.3)	74.4 (33.4)	71.0 (28.9)	53.2 (14.9)	70.0 (20.5)
3–4	85.4 (21.6)	70.6 (35.7)	72.6 (26.6)	55.8 (14.7)	71.1 (18.3)
5 or more	82.3 (24.0)	67.3 (40.1)	69.9 (29.3)	55.9 (15.3)	68.9 (22.5)
F	1.207	1.138	0.312	1.351	0.399
Smokers
Yes	81.7 (25.8)	76.7 (32.6)	74.5 (26.2)	55.5 (13.0)	72.1 (19.0)
No	83.7 (22.8)	69.5 (36.9)	70.5 (28.6)	54.8 (15.4)	69.6 (20.4)
F	0.480	2.774	1.416	0.144	1.057
Comorbidity
Yes	80.4 (20.5)	56.8 (38.9)	60.3 (30.1)	49.2 (14.4)	61.7 (20.7)
No	84.1 (24.3)	75.1 (34.3)	74.5 (26.7)	56.6 (14.7)	72.6 (19.3)
F	1.614	18.315***	18.282***	17.520***	20.982***

*p < 0.050; **p < 0.010; ***p < 0.001. F = F statistics.

Table 4 presents the association between the MC’s health-related quality of life scores and the students’ general characteristics. No significant differences were noted between any of the MC scores and the sex, age, type of the university, and academic year of the students (p > 0.050). However, single students had a significantly higher RE score than those married or engaged. A higher MH score was noted among students attending the faculty of medical sciences compared to other faculties. Smokers had significantly higher VT, SF, and MH scores. Furthermore, students with no comorbidities had significantly higher scores on all of the MC domains.

Table 4.

Association between the health-related quality of life scores of the mental components and the general characteristics of the students.

	Mental components
	VT	SF	RE	MH	Total score
Sex
Man	51.1 (22.4)	56.5 (28.7)	62.9 (33.7)	55.8 (20.9)	56.6 (24.2)
Woman	49.9 (22.0)	59.1 (27.7)	59.4 (34.1)	53.2 (20.5)	55.4 (23.7)
F	0.306	0.849	0.601	1.572	0.234
Age
≤30	50.0 (23.5)	57.3 (28.2)	61.1 (34.1)	54.0 (20.8)	55.6 (24.1)
>30	56.5 (22.0)	63.1 (28.8)	60.5 (31.3)	59.2 (19.1)	59.8 (21.1)
F	2.151	0.964	0.004	1.611	0.764
Marital status
Single	49.8 (22.3)	57.7 (28.1)	63.5 (33.3)	53.9 (20.9)	56.2 (24.1)
Married/Engaged	53.7 (21.2)	58.9 (29.0)	49.0 (35.0)	56.8 (19.8)	54.6 (23.2)
F	1.820	0.116	6.186*	1.090	0.245
University
Public	49.0 (20.6)	60.4 (26.2)	65.1 (32.5)	53.7 (20.0)	57.0 (22.4)
Private	51.1 (22.9)	56.8 (29.1)	59.2 (34.5)	54.7 (21.1)	55.4 (24.5)
F	0.734	1.433	1.576	0.186	0.405
Faculty
Public health	48.5 (20.9)	56.6 (27.8)	65.7 (32.2)	51.4 (14.5)	55.5 (22.9)
Medical sciences	53.2 (22.5)	60.0 (28.2)	61.9 (35.4)	58.3 (13.9)	58.3 (24.8)
Dentistry	53.2 (23.6)	54.8 (27.9)	54.0 (32.8)	56.4 (15.0)	54.6 (25.2)
Pharmacy	47.4 (21.9)	60.2 (29.2)	59.1 (35.5)	52.2 (15.9)	54.7 (23.3)
F	1.802	0.793	1.231	2.779*	0.520
Academic year
1–2	52.8 (21.6)	57.8 (27.6)	63.9 (32.3)	54.6 (20.9)	57.3 (23.1)
3–4	48.9 (21.6)	58.8 (27.3)	62.6 (33.4)	52.9 (20.2)	55.8 (23.5)
5 or more	49.8 (23.7)	56.4 (30.6)	54.4 (36.6)	56.5 (21.3)	54.3 (25.8)
F	1.149	0.227	1.541	1.351	0.440
Smokers
Yes	56.3 (22.0)	63.2 (27.8)	58.4 (34.7)	58.1 (22.0)	59.0 (24.2)
No	48.8 (21.9)	56.4 (28.2)	61.7 (33.7)	53.3 (20.2)	55.1 (23.8)
F	8.093**	4.016*	0.396	3.838*	1.896
Comorbidity
Yes	45.1 (18.9)	47.7 (24.5)	50.4 (34.6)	50.6 (18.5)	48.4 (21.7)
No	51.9 (22.8)	60.8 (28.6)	64.0 (33.3)	55.4 (21.2)	58.0 (24.1)
F	6.770**	15.180***	6.705**	3.691*	11.323***

*p < 0.050; **p < 0.010; ***p < 0.001. F = F statistics.

The combined effect of the predictors affecting the health-related quality of life scores

After adjusting for covariates, it was found that the sex of students did not influence the SF-36 scores and the type of the university (public or private) did not influence any of the MC domains scores. Students older than 30 years had significantly lower scores in all the PC domains while no significance was noted when associating age and any of the MC domains. Married students had a lower RE (b = −12.9) score, and a lower GH (b = −3.6) score was reported among those studying at private universities in comparison to those studying at public universities. Non-smokers had lower VT (b = −8.0) and SF (b = −7.6) scores compared to smokers but a significantly higher MH (b = 5.1) score. Not having any comorbidities had no impact on the PF score but significantly increased all the scores of the remaining domains except the MH (−5.2) score (Table 5). The following equations resulted-in for the assessment of each of the domains:

P F = 94.4 - 10.4 A g e g r o u p > 30

PR = 51.5 - 10.2 A g e g r o u p > 30 + 17.1 N o c o m o r b i t i e s

B P = 60.3 - 11.1 A g e g r o u p > 30 + 12.9 N o c o m o r b i d i t i e s

G H = 51.2 - 2.5 A g e g r o u p > 30 - 3.6 P r i v a t e u n i v e r s i t y + 6.9 N o c o m o r b i d i t i e s

T o t a l P C s c o r e = 61.7 - 8.4 A g e g r o u p + 9.9 N o c o m o r b i d i t i e s

V T = 51.4 - 8 N o n s m o k e r + 7.4 N o c o m o r b i d i t i e s

S F = 47.4 - 7.6 N o n s m o k e r + 13.5 N o c o m o r b i d i t i e s

R E = 54.2 - 12.9 M a r r i e d + 12.3 N o c o m o r b i d i t i e s

M H = 54.5 - 5.2 N o n s m o k e r + 5.1 N o c o m o r b i d i t i e s

T o t a l M C s c o r e = 38.8 + 9.6 N o c o m o r b i d i t i e s

Table 5.

The combined effect of the predictors affecting the health-related quality of life scores.

	Physical components
Parameter	PF	PR	BP	GH	Total score
Parameter	B [95% CI]	B [95% CI]	B [95% CI]	B [95% CI]	B [95% CI]
Intercept	94.4	51.5	60.3	51.2	61.7
	[84.4–104.5]	[27.9–7.2]	[41.9–78.6]	[40.4–62.1]	[48.6–74.8]
Sex (Man vs. Woman)
Age (≤30 Vs > 30)	−10.4* [−19.6– −1.3]	−10.2 [−24.3–3.9]	−11.1* [−22.0–0.1]	−2.5 [−8.3–3.4]	−8.4* [−16.3– −0.7]
Marital status (Single vs Married/Engaged)
University (Public vs Private)				−3.6* [−6.6– −0.5]
Smoking (Yes vs No)
Chronic diseases		17.1***	12.9***	6.9***	9.9***
(Yes vs No)		[8.5–25.6]	[6.2–19.5]	[3.4–10.5]	[5.1–14.6]
R square (%)	12%	49%	53%	57%	61%
	Mental components
	VT	SF	RE	MH	Total score
Parameter	B [95% CI]	B [95% CI]	B [95% CI]	B [95% CI]	B [95% CI]
Intercept	51.4	47.4	54.2	54.5	38.8
	[38.7–64.2]	[31.2–63.5]	[29.8–78.5]	[42.4–66.5]	[28.6–49.1]
Sex (Man vs Woman)
Age (≤30 Vs > 30)
Marital status (Single vs Married/Engaged)			−12.9* [−24.3– −1.5]
University (Public vs Private)
Smoking (Yes vs No)	−8.0** [−13.1– −2.8]	−7.6* [−14.2– −1.1]		−5.2* [−10.0– −0.3]
Chronic diseases	7.4**	13.5***	12.3*	5.1*	9.6***
(Yes vs No)	[2.2–12.6]	[6.9–20.0]	[1.9–22.6]	[0.2–10.0]	[4.0–15.2]
R square (%)	39%	49%	29%	20%	28%

Results are presented as B [95% confidence interval (CI)]. *p < 0.050; **p < 0.010; ***p < 0.001.

Discussion

The present study aimed to assess the health-related QOL of medical students in Lebanon during the COVID-19 pandemic. The study sample included more women than men, two-thirds from private universities and the rest from public ones. Overall, the PC domains had higher scores than the MC domains. Among the PCs, students had higher PF and lower GH scores; among the MC, a higher score was noted for RE and a lower score for VT. Those aged 30 years or less had higher scores in all the PC domains than older students but comparable scores in the MC domains. Single students had a significantly higher RE score and those studying in public universities had greater GH scores. Those in the faculty of medical sciences had significantly higher MH scores compared to other faculties attendants. When testing the combined effect of the different predictors, younger age significantly increased most of the health-related PC scores and having chronic diseases decreased all the QoL scores except the MH score. Furthermore, being a smoker positively impacted the VT and SF of students and negatively influenced their MH.

Based on the values of the skewness of scores (Table 1), the data were normally distributed and converged to their expected values (Hatem et al., 2022). Overall, students’ mental health was more affected than their physical health, in agreement with other studies carried out in similar settings during the pandemic (Qiu et al., 2019; Thomas et al., 2021; Kosilov et al., 2021). In the pre-pandemic period, the MC scores were higher than in this study (Sabbah et al., 2013), which can highlight its impact on medical students’ mental health. Several studies also reported this finding showing the psychological distress among students in addition to their deteriorated emotional states (Passos et al., 2022; Taylor et al., 2022; Yabuki et al., 2022). The long-term consequences of this decline may affect medical students’ academic and professional performance and call for the need to support this sensitive group psychologically. Low GH scores were observed, indicating that medical students’ physical health also deteriorated. The excessive working hours, getting infected, and sleep disorders could have induced poorer general health (Bazan et al., 2021; Mehta et al., 2021). Furthermore, their vitality and SF scores were lower than the previously reported ones. Social isolation and consecutive lockdowns could have significantly impacted their interaction and incorporation within society (Leal Filho et al., 2021).

Students’ sex was not influencing any of the QoL domains, in contrast with a previous study showing that women had higher scores than men in the general and psychological domains (Baceviciene and Jankauskiene, 2021). Those 30 years and younger had significantly higher scores in the physical domains than their older peers, possibly due to their lower level of responsibility and obligations. The existence of comorbidities adversely impacted students’ physical and mental well-being. A result that was previously shown in a similar setting (Jenkins et al., 2021) highlighting the necessity of giving this specific population additional support. The combined effects model showed that older students and those with chronic diseases mainly had lower scores, while only comorbidities affected the overall mental domains.

This study has limitations. Selection bias may have been induced since the data collectors randomly selected students, and possibly only motivated ones were willing to participate. Nevertheless, uniform training was provided to pharmacists who used the same data collection form to reduce this bias, and a different researcher performed data coding and analysis. Recall bias may have also arisen since data collection was performed at the end of the academic year. The study sample was relatively small, which might not allow the extrapolation of the findings to all medical students. Nonetheless, the present study is the first one performed in public and private universities to explore the health-related QoL of medical students during the pandemic.

Conclusion

The QoL of medical students during the COVID-19 pandemic was negatively affected, particularly their mental health. The long-term effect of this impact can affect students’ abilities and academic performance. Age, faculties attended, comorbidities, and smoking status were the main covariates of the health-related QoL scores. Future investigations are recommended to explore the reasons and provide viable solutions to improve the QoL of medical students.

Footnotes

Acknowledgements

We thank Dr. Mathijs Goossens for his assistance with data analysis and his comments that significantly improved the manuscript.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethics approval and consent to participate

The study protocol and tool were reviewed and approved by the institutional review board of the Lebanese University faculty of pharmacy. Written informed consent was obtained from every participant.

ORCID iD

Georges Hatem

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